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Record W1998734719 · doi:10.1017/s1355770x02000062

The impacts of economic reform on the efficiency of silviculture: a non-parametric approach

2002· article· en· W1998734719 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironment and Development Economics · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsData envelopment analysisEconomic efficiencyEconomicsEconomic reformChinaPanel dataProductive efficiencyNatural resource economicsMacroeconomicsEconometricsPolitical scienceMarket economyProduction (economics)Mathematics

Abstract

fetched live from OpenAlex

Institutions and organizations are regarded as being important in determining the efficiency of economic agents and public units. This study first reviews the economic reforms in silvicultural activities in China's state-owned forestry bureaux, then empirically examines the impact of economic reforms. Panel data from 40 forestry bureaux in Heilongjiang Province, and two different economic regimes: from the pre-reform and economic transition periods, are analyzed by Data Envelopment Analysis (DEA). The technical efficiency has been decomposed into pure technical efficiency and scale efficiency and then examined. Our results show that the economic reforms have increased efficiency on average by about 25 per cent. Moreover, the study qualitatively analyses the sources of improvement and argues that the efficiency gain is a result of reductions in labour shirking and administration costs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.176
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it